Bike Rental & Guided Tours

Welcome to Amsterdam, welcome to MacBike. You see much more from the seat of a bike! Cycling is the most economical, sustainable and fun way to explore the city, with its beautiful canals, parks, squares and countless lights. You can also bike along lovely landscapes outside of Amsterdam.

Why MacBike

MacBike has been around for almost 30 years and is the biggest bicycle rental company in Amsterdam. With over 2,500 bikes stored in our five rental shops at strategic locations, we make sure there is always a bike available for you. We offer the newest bicycles in a wide variety, including basic bikes with foot brake (刹车), bikes with hand brake and gears (排挡), bikes with child seats, and children’s bikes.

Prices

Guided City Tours

The 2.5-hour tour covers the Gooyer Windmill, the Skinny Bridge, the Rijksmuseum, Heineken Brewery and much more. The tour departs from Dam Square every hour on the hour, starting at 1:00 pm every day. You can buy your ticket in a MacBike shop or book online.

Quantum ( 量子 ) computers have been on my mind a lot lately. A friend has been sending me articles on how quantum computers might help solve some of the biggest challenges we face as humans. I’ve also had exchanges with two quantum-computing experts. One is computer scientist Chris Johnson who I see as someone who helps keep the field honest. The other is physicist Philip Taylor.

For decades, quantum computing has been little more than a laboratory curiosity. Now, big tech companies have invested in quantum computing, as have many smaller ones. According to Business Weekly, quantum machines could help us “cure cancer, and even take steps to turn climate change in the opposite direction.” This is the sort of hype ( 炒作 ) that annoys Johnson. He worries that researchers are making promises they can’t keep. “What’s new,” Johnson wrote, “is that millions of dollars are now potentially available to quantum computing researchers.”

As quantum computing attracts more attention and funding, researchers may mislead investors, journalists, the public and, worst of all, themselves about their work’s potential. If researchers can’t keep their promises, excitement might give way to doubt, disappointment and anger, Johnson warns. Lots of other technologies have gone through stages of excitement. But something about quantum computing makes it especially prone to hype, Johnson suggests, perhaps because “‘quantum’ stands for something cool you shouldn’t be able to understand.” And that brings me back to Taylor, who suggested that I read his book Q for Quantum.

After I read the book, Taylor patiently answered my questions about it. He also answered my questions about PyQuantum, the firm he co-founded in 2016. Taylor shares Johnson’s concerns about hype, but he says those concerns do not apply to PyQuantum.

The company, he says, is closer than any other firm “by a very large margin ( 幅度 )” to building a “useful” quantum computer, one that “solves an impactful problem that we would not have been able to solve otherwise.” He adds, “People will naturally discount my opinions, but I have spent a lot of time quantitatively comparing what we are doing with others.”

Could PyQuantum really be leading all the competition “by a wide margin”, as Taylor claims? I don’t know. I’m certainly not going to advise my friend or anyone else to invest in quantum computers. But I trust Taylor, just as I trust Johnson.

Superhuman artificial intelligence is already among us. Well, sort of. When it comes to playing games like chess and Go, or solving difficult scientific challenges like predicting protein structures, computers are well ahead of us. But we have one superpower they aren’t close to mastering: mind reading.

Humans have a mysterious ability to reason the goals, desires and beliefs of others, a crucial skill that means we can anticipate other people’s actions and the consequences of our own. Reading minds comes so easily to us, though, that we often don’t think to spell out what we want. If AIs are to become truly useful in everyday life—to cooperate effectively with us or to understand that a child might run into the road after a bouncing ball—we have to give them this gift that evolution has given us to read other people’s minds.

Psychologists refer to the ability to infer another’s mental state as theory of mind. In humans, this capacity starts to develop at a very young age. How to reproduce the capability in machines is far from clear, though. One of the main challenges is context. For instance, if someone asks whether you are going for a run and you reply “it’s raining”, they can quickly conclude that the answer is no. But this requires huge amounts of background knowledge about running, weather and human preferences.

Moreover, whether humans or AI, the theory of mind is supposed to emerge naturally from one’s own learning process. Building prior knowledge into AI makes it reliant on our imperfect understanding of theory of mind. In addition, AI may be capable of developing approaches we could never imagine. There can be many forms of theory of mind that we don’t know about simply because we live in a human body that has certain types of senses and a certain ability to think.

Yet we might still want AI to have a more human-like form of theory of mind. Humans can clearly explain their goals and desires to each other using common language and ideas. While letting AI form the theory of mind in their learning process is likely to lead to developing more powerful AI, plainly building in shared ways to represent knowledge may be crucial for humans to trust and communicate with AI.

It is important to remember, though, that the pursuit of machines with theory of mind is about more than just building more useful robots. It is also a stepping stone on the path towards a deeper goal for AI and robotics research: building truly self-aware machines. Whether we will ever get there remains to be seen. But along the way thinking about other people and other agents, we are on the path to learning to think about ourselves.